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Over the last fifty years, game theory has evolved from a mathematical theory of optimal behaviour in stylized situations (“games”) to a general theory of human behaviour, be it actually observed or normatively desirable. Its scope includes both the mathematical modelling and analysis

Over the last fifty years, game theory has evolved from a mathematical theory of optimal behaviour in stylized situations (“games”) to a general theory of human behaviour, be it actually observed or normatively desirable. Its scope includes both the mathematical modelling and analysis of competition and conflict and the study of human behaviour in strategic contexts and its determinants. Nowadays, game theory has become the language of economics and is increasingly becoming one of the main methods of analysis in several social sciences. Its theoretical underpinnings can be viewed as a mathematical subdiscipline, while its more behavioural offshoots benefit from cross-fertilization with psychology. Game theory has grown within economics but is, by its very nature, interdisciplinary, to the extent that no game theorist can or should define him or herself in disciplinary terms anymore. [...]
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We introduce a class of evolutionary game dynamics — pairwise comparison dynamics — under which revising agents choose a candidate strategy at random, switching to it with positive probability if and only if its payoff is higher than the agent’s current strategy. We

We introduce a class of evolutionary game dynamics — pairwise comparison dynamics — under which revising agents choose a candidate strategy at random, switching to it with positive probability if and only if its payoff is higher than the agent’s current strategy. We prove that all such dynamics satisfy Nash stationarity: the set of rest points of these dynamics is always identical to the set of Nash equilibria of the underlying game. We also show how one can modify the replicator dynamic and other imitative dynamics to ensure Nash stationarity without increasing the informational demands placed on the agents. These results provide an interpretation of Nash equilibrium that relies on large numbers arguments and weak requirements on payoff observations rather than on strong equilibrium knowledge assumptions.
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Explaining human cooperation in large groups of non-kin is a major challenge to both rational choice theory and the theory of evolution. Recent research suggests that group cooperation can be explained by positing that cooperators can punish non-cooperators or cheaters. The experimental evidence

Explaining human cooperation in large groups of non-kin is a major challenge to both rational choice theory and the theory of evolution. Recent research suggests that group cooperation can be explained by positing that cooperators can punish non-cooperators or cheaters. The experimental evidence comes from public goods games in which group members are fully informed about the behavior of all others and cheating occurs in full view. We demonstrate that under more realistic information conditions, where cheating is less obvious, punishment is much less effective in enforcing cooperation. Evidently, the explanatory power of punishment is constrained by the visibility of cheating.
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Experimental and empirical evidence shows that the utility an individual derives from a certain state depends on the reference state she compares it to. According to economic theory, the reference state is determined by past, present and future outcomes of either the individual

Experimental and empirical evidence shows that the utility an individual derives from a certain state depends on the reference state she compares it to. According to economic theory, the reference state is determined by past, present and future outcomes of either the individual herself or her reference group. The experiment described in this paper suggests that, in addition, reference states depend to a significant degree on environmental factors not relevant for outcomes. It indicates that reference states - and hence utility - can relatively easily be influenced without changing people’s outcomes, e.g., through priming.
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Game and decision theory start from rather strong premises. Preferences, represented by utilities, beliefs represented by probabilities, common knowledge and symmetric rationality as background assumptions are treated as “given.” A richer language enabling us to capture the process leading to what is “given”

Game and decision theory start from rather strong premises. Preferences, represented by utilities, beliefs represented by probabilities, common knowledge and symmetric rationality as background assumptions are treated as “given.” A richer language enabling us to capture the process leading to what is “given” seems superior to the stenography of decision making in terms of utility cum probability. However, similar to traditional rational choice modeling, boundedly rational choice modeling, as outlined here, is far from being a “global” theory with empirical content; rather it serves as a tool to formulate “local” theories with empirical content.
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